activity
20182026
most citedDeep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale

210 citations · 233 across the 10 of their papers we have counts for

collaborators

10 papers

cs.AI2026

An AI agent for treatment reasoning over a biomedical tool universe

Shanghua Gao, Ayush Noori, Richard Zhu +13

Treatment reasoning underpins every therapeutic decision, integrating disease context, comorbidities, medications, contraindications, and evolving biomedical knowledge to select an…

cs.DC2024★ 6 cited

Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services

Dhavalkumar Patel, Ganesh Raut, Satya Narayan Cheetirala +5

Generative AI is transforming enterprise application development by enabling machines to create content, code, and designs. These models, however, demand substantial computational…

q-bio.MN2023

Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning

Sonish Sivarajkumar, Pratyush Tandale, Ankit Bhardwaj +6

Transcription factors (TFs) play a vital role in the regulation of gene expression thereby making them critical to many cellular processes. In this study, we used graph machine lea…

cs.LG2021★ 8 cited

Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data

Tingyi Wanyan, Jing Zhang, Ying Ding +3

Electronic Health Record (EHR) data has been of tremendous utility in Artificial Intelligence (AI) for healthcare such as predicting future clinical events. These tasks, however, o…

cs.CV2021

Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop

Yan Han, Chongyan Chen, Ahmed Tewfik +4

Building a highly accurate predictive model for classification and localization of abnormalities in chest X-rays usually requires a large number of manually annotated labels and pi…

cs.LG2020

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records

Tingyi Wanyan, Hossein Honarvar, Ariful Azad +2

Computational prediction of in-hospital mortality in the setting of an intensive care unit can help clinical practitioners to guide care and make early decisions for interventions.…

q-bio.QM2020★ 210 cited

Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale

Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee +6

Deriving disease subtypes from electronic health records (EHRs) can guide next-generation personalized medicine. However, challenges in summarizing and representing patient data pr…

cs.LG2018★ 4 cited

Time Aggregation and Model Interpretation for Deep Multivariate Longitudinal Patient Outcome Forecasting Systems in Chronic Ambulatory Care

Beau Norgeot, Dmytro Lituiev, Benjamin S. Glicksberg +1

Clinical data for ambulatory care, which accounts for 90% of the nations healthcare spending, is characterized by relatively small sample sizes of longitudinal data, unequal spacin…

cs.CV2018

Deep Learning Predicts Hip Fracture using Confounding Patient and Healthcare Variables

Marcus A. Badgeley, John R. Zech, Luke Oakden-Rayner +7

Hip fractures are a leading cause of death and disability among older adults. Hip fractures are also the most commonly missed diagnosis on pelvic radiographs. Computer-Aided Diagno…

cs.CY2018★ 5 cited

Processing of Electronic Health Records using Deep Learning: A review

Venet Osmani, Li Li, Matteo Danieletto +3

Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of heal…